基于EMD-SVM的刚性罐道故障诊断研究

Research on Fault Diagnosis for Rigid Guide Based on EMD-SVM

探讨了基于经验模态分解(EMD)和支持向量机(SVM)的提升机刚性罐道故障诊断方法。首先利用EMD对采集的振动信号进行分解以获得内蕴模态函数(IMF),并结合小波降噪对其高频分量进行降噪。然后,提取降噪后IMF分量中的典型信息作为故障特征向量,使用SVM进行故障模式识别。

Discusses a fault diagnosis method for rigid cage guide of shaft hoist, based on Empirical Mode Decomposition（EMD） and Support Vector Machine（SVM）. Firstly, the EMD is used to decompose the acquired vibration signal to obtain Intrinsic Mode Function（IMF）, also with wavelet denoising method used to denoise its high-frequency components. Then, typical information in IMF components after the denoising are extracted as fault characteristic vectors, and recognition of fault pattern is made using SVM.